Research Methods in Psychology

Research methods provide the framework for asking questions, collecting data, analyzing findings, and drawing conclusions that are both reliable and valid. Mastery of these methods is not merely an academic exercise; it is the bedrock of evidence-based practice and the engine of psychological progress.

Positivism and Post-Positivism

Positivism, rooted in the natural sciences, posits that there is an objective reality that can be known through empirical observation and logical deduction. Post-positivism acknowledges that while an objective reality exists, human perception and measurement are inherently imperfect and prone to bias.

Constructivism

Constructivism argues that reality is not objective but rather socially constructed through individual and collective interpretation. Knowledge is seen as subjective and context-dependent.

Critical Theory

Critical theory explicitly incorporates a focus on power dynamics, social injustice, and emancipation. Researchers seek not only to understand social realities but also to critique and transform them.

The scientific method provides a systematic approach to acquiring knowledge through observation, hypothesis formulation, experimentation, data analysis, conclusion, communication, and replication.

Basic research aims to expand fundamental knowledge without immediate practical application. Applied research seeks to solve practical problems and improve human conditions.

True Experiments

A true experiment is characterized by: (1) manipulation of the IV, (2) random assignment, and (3) control of extraneous variables.

Quasi-Experiments

Quasi-experiments resemble true experiments but lack random assignment. This limits causal inference due to potential selection bias and confounding variables.

Single-Subject Designs

These designs focus on intense study of individual participants, often used in clinical psychology and applied behavior analysis. Common designs include ABA reversal and multiple baseline designs.

Correlational Studies

Correlation does not equal causation. Correlational studies examine statistical relationships without manipulation. The directionality problem and third-variable problem limit causal inferences.

Observational Studies

Researchers systematically observe and record behavior in natural or structured settings. Types include naturalistic observation, participant observation, and structured observation.

Survey Research

Collecting data by asking participants to self-report on attitudes, beliefs, or behaviors. Susceptible to response biases like social desirability bias.

Case Studies

In-depth investigation of a single individual, group, or event. Provides rich detail but has limited generalizability (e.g., Phineas Gage, H.M.).

Levels of Measurement

Inferential Statistics

p-value < .05 is conventionally considered statistically significant. Effect sizes (e.g., Cohen's d) quantify the magnitude of observed effects.

Probability Sampling Methods

Every member has a known chance of selection. Includes simple random, systematic, stratified random, and cluster sampling.

Non-Probability Sampling Methods

Members do not have known chance of selection. Includes convenience, quota, purposive, and snowball sampling. Results have limited generalizability.

Research methods are the backbone of evidence-based practice (EBP) in psychology. Rigorous experimental designs (e.g., RCTs) test therapy effectiveness and inform DSM-5 treatment guidelines.

The Replication Crisis and Open Science

The replication crisis revealed that many published findings could not be reproduced. This led to the open science movement including pre-registration, open data, and transparency practices to prevent p-hacking and HARKing.

Qualitative vs. Quantitative Divide

Quantitative emphasizes measurement and statistical analysis. Qualitative focuses on understanding meaning and context. Mixed methods combine both approaches.

WEIRD Samples and Cultural Sensitivity

Much research relies on Western, Educated, Industrialized, Rich, Democratic (WEIRD) samples, raising concerns about external validity. Cross-cultural research and diverse samples are increasingly emphasized.

What is the main difference between internal and external validity?

Internal validity refers to the extent to which a study can confidently establish a cause-and-effect relationship between the independent and dependent variables, free from confounding factors. External validity refers to the generalizability of the study's findings to other populations, settings, and times. A study can have high internal validity but low external validity, and vice-versa.

Why is random assignment so important in experiments?

Random assignment is crucial because it helps ensure that the experimental groups are equivalent at the beginning of the study on all possible variables, both known and unknown. This minimizes the influence of confounding variables, making it more likely that any observed differences in the dependent variable are truly due to the manipulation of the independent variable, thus increasing internal validity.

Can qualitative research be considered scientific?

Yes, absolutely. While it differs from quantitative research in its epistemological assumptions and methods, qualitative research employs systematic and rigorous approaches to data collection and analysis. It aims to provide in-depth understanding, explore complex phenomena, and generate hypotheses, contributing to scientific knowledge. Its "scientific-ness" is often judged by criteria like trustworthiness (credibility, transferability, dependability, confirmability) rather than statistical significance.

What is the "replication crisis" and what are its implications?

The replication crisis refers to the alarming discovery that many published findings in psychology (and other sciences) could not be consistently reproduced when studies were repeated. This has led to concerns about the reliability of published research. Its implications include a push for greater methodological rigor, transparency (e.g., open science practices like pre-registration and data sharing), and a re-evaluation of how research is conducted, reported, and rewarded.

When should I use a t-test versus an ANOVA?

You use a t-test when you want to compare the means of two groups (e.g., comparing the anxiety scores of a treatment group vs. a control group). You use an ANOVA (Analysis of Variance) when you want to compare the means of three or more groups (e.g., comparing anxiety scores across low-dose, medium-dose, and high-dose medication groups) or when you have multiple independent variables. ANOVA helps avoid the inflated Type I error rate that would occur if multiple t-tests were run.

What's the difference between a mediator and a moderator?

A mediator variable explains how or why an independent variable affects a dependent variable. It acts as an intervening step in the causal chain (e.g., stress (IV) leads to burnout (DV) via emotional exhaustion (mediator)). A moderator variable influences the strength or direction of the relationship between an independent and dependent variable. It changes when or for whom an effect occurs (e.g., social support (moderator) might lessen the impact of stress (IV) on well-being (DV)).